code: def benchmark(train_x_df, train_y_df):
      """Benchmark the time required to predict on the `bench_prediction` data."""
      model, x = predict_preamble(train_x_df, train_y_df)
  
      total_duration = 0
      for _ in range(0, bench_prediction):
          start = time.time()
          model.predict(x)
          end = time.time()
          duration = end - start
  
          total_duration = total_duration + duration
  
      print("Total Duration:", total_duration)
      print(
          "Avg Runtime:", total_duration / bench_prediction * 1000, "ms"
      )
  
file_path: tf-encrypted/examples/application/house-credit-default/main.py
imports: import argparse
  import os
  import time
  import tensorflow
  import tf2onnx
  from tensorflow import keras
  from tensorflow.keras import layers
  from tensorflow.python import errors_impl
  from utils import data_prep
  from utils import read_one_row
label_desc: Use image node_id 7 for calling a global function with example usage: benchmark(train_x_df, train_y_df) without return types